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mixed integer non-linear programming model for reliable and safer design at an early stage

COMPUTERS & CHEMICAL ENGINEERING 2021年 147卷 107256-107256页

作者： Vazquez, Daniel Ruiz-Femenia, Ruben Caballero, Jose A. Univ Alicante Inst Chem Proc Engn PO 99 E-3080 Alicante Spain

We present a mixed integer non-linear programming (MINLP) model capable of choosing the best design considering economic profit, availability, and safety. The model takes into account the probability of suffering a failure in a year of operation, as well as the revenue generated and the probability of the process units of being in a non-functional state. The inclusion of programmed maintenances of a specified duration is considered in the model, assuming an equal distribution in the maintenances time. The performance of the model is illustrated by small examples to help the reader to better understand the model, before applying it to the methanol synthesis case study, where the economic and safety objectives are represented in a Pareto front. The results showcase the possibility of considering safety during the early design stage. ? 2021 Elsevier Ltd. All rights reserved.

关键词： Reliability Process safety mixed integer non-linear programming

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Solving energy transportation cost using mixed integer non-linear programming

Solving energy transportation cost using mixed integer non-l...

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International Symposium on Advanced Electrical and Communication Technologies (ISAECT)

作者： El-Harrouti, Taoufiq El Kafazi, Ismail Bannari, Rachid Amar, Sara Haddou Abouabdillah, Abdellah Ibn Tofail Univ Lab Syst Engn Ensa Kenitra Morocco

ISBN: (纸本)9781538673287

Analysis of the energy transportation cost has a wide range of scope nowadays. Satisfying the demand for minimum cost is a great challenge for the power system. The planning and modeling of the production system should put forward the objectives of greenhouse gas emission reduction and promote the deployment of renewable energy. These objectives are designed to achieve significant energy savings in the future. In this work, a mixed integer non-linear programming is used to minimize the energy transportation cost using commercial software GAMS. The obtained results show the effectiveness of the proposed method.

关键词： Optimization transportation cost mixed integer non-linear programming scheduling demand

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Reliability-Security Constrained Unit Commitment Based on Benders Decomposition and mixed integer non-linear programming 1

Reliability-Security Constrained Unit Commitment Based on Be...

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International Conference on Computer Communications and Electronics (Comptelix)

作者： Gupta, Pranda Prasanta Jain, Prerna Sharma, Suman Bhakar, Rohit Malaviya Natl Inst Technol Dept Elect Engn Jaipur Rajasthan India

ISBN: (纸本)9781509047086

Reliability-Security Constrained Unit Commitment (RSCUC) with emphasis on mixed integer nonlinear programming (MINLP) and Benders Decomposition (BD) based on thermal generating units are presented in this paper. To solve unit commitment problem generalized BD along with reliability issues are considered. The approach presented in this work allows the decomposition of the whole program in quadratic mixed integer master program and network security check non-linear subproblem. The case study demonstrates the effectiveness of the proposed approach.

关键词： Security-constrained unit commitment Benders decompostion mixed integer non-linear programming reliabilty issues

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Formulation and solution of distribution system voltage and VAR control with distributed generation as a mixed integer non-linear programming problem

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ELECTRIC POWER SYSTEMS RESEARCH 2014年第Mar.期108卷 164-169页

作者： Paaso, Esa A. Liao, Yuan Cramer, Aaron M. Univ Kentucky Dept Elect & Comp Engn Lexington KY 40506 USA

Coordinated voltage and VAR control (VVC) can provide major economic benefits for distribution utilities. Incorporating distributed generations (DG) for VVC can improve the efficiency and reliability of distribution systems. This paper presents an approach to formulate and solve distribution system VVC with DG units as a mixed integer non-linear programming (MINLP) problem. The method can be utilized to create an effective control scheme for both the traditional VVC devices and DG units. The MINLP formulation is based on three-phase power flow formulation, and is solved with an open-source BONMIN optimization solver with outer approximation (OA) algorithm. BONMIN is interfaced with Matlab via a third-party optimization toolbox. The proposed approach is applied to several distribution feeder models with promising results. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Distributed generation mixed integer non-linear programming Outer approximation Reactive power control Voltage control

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mixed integer non-linear programming and Artificial Neural Network based approach to ancillary services dispatch in competitive electricity markets

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APPLIED ENERGY 2013年 108卷 261-270页

作者： Canizes, Bruno Soares, Joao Faria, Pedro Vale, Zita Polytech Porto IPP GECAD Knowledge Engn & Decis Support Res Ctr P-4200072 Oporto Portugal

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids;(2) dispatch considering complex bids. (c) 2013 Elsevier Ltd. All rights reserved.

关键词： Ancillary services Artificial Neural Networks Electricity markets linear programming mixed integer non-linear programming Power systems

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Signal optimization at an isolated intersection under cyclic vehicle arrivals using spatially sparse trajectory data

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2024年 163卷

作者： Wan, Lijuan Ma, Wanjing Lo, Hong K. Yu, Chunhui Hong Kong Univ Sci & Technol Dept Civil & Environm Engn Hong Kong Peoples R China Tongji Univ Key Lab Rd & Traff Engn Minist Educ 4800 Caoan Rd Shanghai 201804 Peoples R China

Existing trajectory -based signal timing studies either assume time -invariant vehicle arrivals or require high penetration rates of connected vehicles (CVs). However, vehicle arrivals at an urban intersection typically follow a cyclic pattern in the real world due to the impacts of traffic signals at upstream signalized intersections. And the penetration rates of CVs are likely to remain at low levels in the near future. This study develops two time -slot based signal optimization models for isolated intersections under cyclic vehicle arrivals using spatially sparse CV trajectories. The number of sub -cycles within a generalized cycle, along with phase sequence, cycle length, and green splits in each sub -cycle, is optimized. The minimization of the weighted sum of oversaturated phase numbers and total vehicle delays is used as the objective function taking into consideration both under- and over -saturated traffic. The consideration of the over -saturated phase number is to increase vehicle throughput and reduce queue length. The cyclicity of vehicle arrivals is identified by Autocorrelation Function with the aid of the aggregation of spatially sparse trajectories. An aggregated -trajectory -based mixed -integer linear programming model is formulated to estimate the shockwaves under the initial signal timing plan. The evolution of shockwaves with varying signal timings is predicted based on the estimated profiles of queueing shockwave speeds under the cyclic demand as well as total vehicle delay and residual queue length. Two mixed integer non-linear programming models are formulated to optimize the time -slot based signal schemes with a fixed and a flexible cycle structure. Aggregated -trajectoryinformed Monte Carlo Tree Search (ATI-MCTS) and Dynamic programming (DP) algorithms are designed for solutions, respectively. Numerical studies validate the advantages of the proposed models over the one in Synchro Studio, vehicle -actuated control, and longest -queue -fi

关键词： Time-slot based signal scheme Spatially sparse trajectory data Cyclic vehicle arrival Traffic shockwave mixed integer non-linear programming

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Strategic supply and transportation planning of a supply chain for agricultural biomass to hydrogen and syngas

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 197卷

作者： Nugroho, Yohanes Kristianto Zhu, Liandong Univ Southern Denmark Inst Technol & Innovat Odense Denmark Wuhan Univ Hubei Key Lab Biomass Resource Chem & Environm Bio Sch Resources & Environm Sci Wuhan 430079 Peoples R China Wuhan Univ Hubei Int Sci & Technol Cooperat Base Sustainable Wuhan 430079 Peoples R China

Strategic supply and transportation planning of agricultural biomass to hydrogen and syngas supply chain with inter-fuel and inter-biomass substitution was studied in this paper. The sourcing and transportation decision was modeled, according to bi-level optimization, where suppliers competed on supply capacity by maximizing their profits at minimum transportation and holding cost. Considering supply chain superstructure, dual biomass suppliers were modeled to supply a biofuel producer who produced two different types of biofuels. The supply planning was combined with transportation planning to minimize total supply chain costs. The results showed that the model was capable of finding optimum purchase and selling prices and production capacity, by maximizing inter-fuel and inter-biomass substitutability. Another key finding was that the proposed model was capable of finding optimum order allocation to both biomass suppliers in such a way that there was an equal profit distribution between suppliers and biofuel producers.

关键词： Biomass Dual sourcing mixed integer non-linear programming Transportation planning Bi-level optimization Equal profit distribution

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Designing a two-stage model for the resilient agri-food supply chain network under dynamic competition

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BRITISH FOOD JOURNAL 2024年第2期126卷 662-681页

作者： Li, Zhuyue Zhang, Chunxiao Shandong Univ Jinan Peoples R China Ocean Univ China Qingdao Peoples R China

PurposeSupply chain risk management can effectively reduce the loss of retailers. In this regard, retailers need to consider the competition risks of competitors in addition to the disruption risks. This paper designs a resilient retail supply chain network for perishable foods under the dynamic competition to maximize retailer's ***/methodology/approachA two-stage mixed-integer non-linear model is presented for designing the supply chain network. In the first stage, an equilibrium model that considers the characteristics of perishable foods is developed. In the second stage, a mixed integer non-linear programming model is presented to deal with the strategic decisions. Finally, an efficient memetic algorithm is designed to deal with large-scale *** optimal the selection of suppliers, distribution centers and the order allocation are found among the supply chain entities. Considering the perishability of agri-food products, the equilibrium retail price and selling quantity are determined. Through a numerical example, the optimal inventory period under different maximum shelf life and the impact of three resilient strategies on retailer's profit, selling price and selling quantity are *** limitations/implicationsAs for future research, the research can be extended in a number of directions. First, this paper studies the retail supply chain network design problem under competition among retailers. It can be an interesting direction to consider retailers competing with suppliers. Second, the authors can try to linearize the non-linear model and solve the large-scale integer programming problem by exact algorithm. Finally, the freshness of perishable foods gradually declines linearly to zero as the maximum shelf life approaches, and it would be a meaningful attempt to consider the freshness of perishable foods declines ***/valueThis paper innovatively designs the resilient supply chain network for perishabl

关键词： Competitive supply chain network design Supply chain disruptions Supplier selection mixed integer non-linear programming

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A general purpose exact solution method for mixed integer concave minimization problems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第3期309卷 977-992页

作者： Sinha, Ankur Das, Arka Anand, Guneshwar Jayaswal, Sachin Indian Inst Management Ahmedabad Prod & Quantitat Methods Ahmadabad 380015 Gujarat India Indian Inst Management Visakhapatnam Prod & Operat Management Visakhapatnam 530003 Andhra Pradesh India

In this article, we discuss an exact algorithm for solving mixed integer concave minimization problems. A piecewise inner-approximation of the concave function is achieved using an auxiliary linear program that leads to a bilevel program, which provides a lower bound to the original problem. The bilevel program is reduced to a single level formulation with the help of Karush-Kuhn-Tucker (KKT) conditions. Incorporating the KKT conditions lead to complementary slackness conditions that are linearized using BigM, for which we identify a tight value for general problems. Multiple bilevel programs, when solved over iterations, guarantee convergence to the exact optimum of the original problem. Though the algorithm is general and can be applied to any optimization problem with concave function(s), in this paper, we solve two common classes of operations and supply chain problems;namely, the concave knapsack problem, and the concave production-transportation problem. The computational experiments indicate that our proposed approach outperforms the customized methods that have been used in the literature to solve the two classes of problems by an order of magnitude in most of the test cases.(c) 2023 Elsevier B.V. All rights reserved.

关键词： Global optimization Concave minimization mixed integer non-linear programming Knapsack problem Production -transportation problem

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Real-Time Dispatching and Operation Management of Battery Swapping Stations With Uncertain Demand via Deep Reinforcement Learning

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年第6期26卷 8583-8601页

作者： Wu, Shangtao Cen, Yuhao Luo, Xiongwei Pei, Mingyang South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510641 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China South China Univ Technol Sch Math Guangzhou 510641 Peoples R China

Electric vehicle charging stations are widespread but suffer from long charging times. In contrast, battery swapping stations have gained attention due to their efficiency and small footprint. However, there is a lack of extensive discussion on their layout, operation modes, and scheduling algorithms. This paper discusses the layout-dispatching-scheduling model of battery swapping stations and super battery swapping stations under centralized charging and unified dispatch. Considering battery swapping stations service time and electric vehicles queuing, a queuing-aware location-routing problem is proposed and solved using Gurobi. This study tackles the uncertainty in electric vehicle spatio-temporal dispatch by formulating the battery scheduling process between super battery swapping stations and battery swapping stations as a vehicle routing problem with time windows and uncertain demand. To address this challenge, the study proposes an adaptive routing optimization method based on an improved proximal policy optimization algorithm. Additionally, it investigates a flexible charging strategy for super battery swapping stations, where the battery charging and discharging process is modeled as a Markov decision process. To optimize operational revenue, meet demand, enable grid interactions, and contribute to peak shaving, the study employs a deep reinforcement learning approach that utilizes the twin delayed deep deterministic policy gradient algorithm. The system design is proven to be feasible and capable of meeting operational requirements.

关键词： Batteries Heuristic algorithms Real-time systems Costs Optimization Vehicle routing Job shop scheduling Electricity Vehicle dynamics Dynamic scheduling Battery swapping station mixed integer non-linear programming vehicle routing problem deep reinforcement learning uncertain demand

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